代码搜索：classification
找到约 3,679 项符合「classification」的源代码
代码结果 3,679
www.eeworm.com/read/148342/12474582
m softmargin.m
function y = softmargin(x)
%SOFTMARGIN Support Vector Classification Softmargin
%
% Usage: y = softmargin(x)
%
% Author: Steve Gunn (srg@ecs.soton.ac.uk)
if (nargin ~= 1) % check correct number o
www.eeworm.com/read/248638/12549708
txt introduction.txt
主要是实现调制识别，区分几种常用的数字调制信号。含有两个文件夹 其一为特征参数的仿真；其二为正确识别率的仿真。
文件夹key feature simulink中：
运行程序会得到各特征参数之间区分图 从图中可看到特征参数的有效性，见图。
文件夹<mark>classification</mark> rate simulink中：
运行main.m文件 可以得到 ...
www.eeworm.com/read/146640/12628568
m softmargin.m
function y = softmargin(x)
%SOFTMARGIN Support Vector Classification Softmargin
%
% Usage: y = softmargin(x)
%
% Author: Steve Gunn (srg@ecs.soton.ac.uk)
if (nargin ~= 1) % check correct number o
www.eeworm.com/read/300795/13893021
plg dsplit.plg
Build Log
--------------------Configuration: DSPLIT - Win32 Debug--------------------
Command Lines
Creating temporary file "C:\WINDOWS\TEMP\RS
www.eeworm.com/read/300777/13893702
plg dsplit.plg
Build Log
--------------------Configuration: DSPLIT - Win32 Debug--------------------
Command Lines
Creating temporary file "C:\WINDOWS\TEMP\RS
www.eeworm.com/read/134893/13972154
m contents.m
% Neural Network Design Demonstrations.
% Copyright (c) 1994 by PWS Publishing Company.
%
% General
% nnd - Splash screen.
% nndtoc - Table of contents.
% nnsound - Turn Neural Net
www.eeworm.com/read/106962/15616600
readme
Libsvm is a simple, easy-to-use, and efficient software for SVM
classification and regression. It can solve C-SVM classification,
nu-SVM classification, one-class-SVM, epsilon-SVM regression, and
nu-S
www.eeworm.com/read/291799/8394677
m artmap_classify.m
function classification = ARTMAP_Classify(artmap_network, data)
% ARTMAP_Classify Uses an ARTMAP network to classify the given input data.
% CLASSIFICATION = ARTMAP_Classify(ARTMAP_NETWORK, DA
www.eeworm.com/read/190459/8443115
m deltablssvm.m
function model = deltablssvm(model,a1,a2)
% Bias term correction for the LS-SVM classifier
%
% >> model = deltablssvm(model, b_new)
%
% This function is only useful in the object oriented function
%
www.eeworm.com/read/286662/8751856
m show_algorithms.m
function show_algorithms (type, show_details)
% Specify possible classification algorithms and their details
%
% Inputs:
% type - Can be either classification, preprocessing, or fea